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Advances in public transit modeling and smart card technologies can reveal detailed contact patterns of passengers. A natural way to represent such contact patterns is in the form of networks. In this paper we utilize known contact patterns from a public transit assignment model in a major metropolitan city, and propose the development of two novel network structures, each of which elucidate certain aspects of passenger travel behavior. We first propose the development of a transfer network, which can reveal passenger groups that travel together on a given day. Second, we propose the development of a community network, which is derived from the transfer network, and captures the similarity of travel patterns among passengers. We then explore the application of each of these network structures to identify the most frequently used travel paths, i.e., routes and transfers, in the public transit system, and model epidemic spreading risk among passengers of a public transit network, respectively. In the latter our conclusions reinforce previous observations, that routes crossing or connecting to the city center in the morning and afternoon peak hours are the most "dangerous" during an outbreak.

The mental lexicon stores words and information about words. The lexicon is seen by many researchers as a network, where lexical units are nodes and the different links between the units are connections. Based on the analysis of a word association network, in this article we show that different kinds of associative connections exist in the mental lexicon. Our analysis is based on a word association database from the agglutinative language Hungarian. We use communities – closely knit groups – of the lexicon to provide evidence for the existence and coexistence of different connections. We search for communities in the database using two different algorithms, enabling us to see the overlapping (a word belongs to multiple communities) and non-overlapping (a word belongs to only one community) community structures. Our results show that the network of the lexicon is organized by semantic, phonetic, syntactic and grammatical connections, but encyclopedic knowledge and individual experiences are also shaping the associative structure. We also show that words may be connected not just by one, but more types of connections at the same time.